{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "8116ed1c",
   "metadata": {},
   "outputs": [],
   "source": [
    "# 下载Python中对应的库\n",
    "#  pip install seaborn"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "68214cd9",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import seaborn as sns\n",
    "sns.set_theme(style=\"whitegrid\")\n",
    "tips = sns.load_dataset(\"tips\")\n",
    "ax = sns.barplot(x=\"day\", y=\"total_bill\", data=tips)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "90ceddd8",
   "metadata": {},
   "outputs": [],
   "source": [
    "# 加载分析数据\n",
    "import pandas as pd\n",
    "top3 = pd.read_csv(\"../data/student_score_top3.csv\",names=['student_id','name','age','gender','clazz','score','rank_res'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "3be80bd0",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>student_id</th>\n",
       "      <th>name</th>\n",
       "      <th>age</th>\n",
       "      <th>gender</th>\n",
       "      <th>clazz</th>\n",
       "      <th>score</th>\n",
       "      <th>rank_res</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1500100308</td>\n",
       "      <td>黄初夏</td>\n",
       "      <td>23</td>\n",
       "      <td>女</td>\n",
       "      <td>文科一班</td>\n",
       "      <td>628</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1500100875</td>\n",
       "      <td>马向南</td>\n",
       "      <td>21</td>\n",
       "      <td>女</td>\n",
       "      <td>文科一班</td>\n",
       "      <td>595</td>\n",
       "      <td>2.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1500100943</td>\n",
       "      <td>许昌黎</td>\n",
       "      <td>21</td>\n",
       "      <td>男</td>\n",
       "      <td>文科一班</td>\n",
       "      <td>580</td>\n",
       "      <td>3.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1500100160</td>\n",
       "      <td>云冰真</td>\n",
       "      <td>24</td>\n",
       "      <td>女</td>\n",
       "      <td>文科三班</td>\n",
       "      <td>568</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1500100434</td>\n",
       "      <td>黎雨珍</td>\n",
       "      <td>23</td>\n",
       "      <td>女</td>\n",
       "      <td>文科三班</td>\n",
       "      <td>550</td>\n",
       "      <td>2.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>1500100572</td>\n",
       "      <td>臧忆香</td>\n",
       "      <td>23</td>\n",
       "      <td>女</td>\n",
       "      <td>文科三班</td>\n",
       "      <td>550</td>\n",
       "      <td>3.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>1500100418</td>\n",
       "      <td>蓟海昌</td>\n",
       "      <td>22</td>\n",
       "      <td>男</td>\n",
       "      <td>文科二班</td>\n",
       "      <td>611</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>1500100823</td>\n",
       "      <td>宓新曦</td>\n",
       "      <td>22</td>\n",
       "      <td>男</td>\n",
       "      <td>文科二班</td>\n",
       "      <td>547</td>\n",
       "      <td>2.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>1500100954</td>\n",
       "      <td>咸芷天</td>\n",
       "      <td>21</td>\n",
       "      <td>女</td>\n",
       "      <td>文科二班</td>\n",
       "      <td>533</td>\n",
       "      <td>3.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>1500100930</td>\n",
       "      <td>闻运凯</td>\n",
       "      <td>24</td>\n",
       "      <td>男</td>\n",
       "      <td>文科五班</td>\n",
       "      <td>589</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>1500100949</td>\n",
       "      <td>颜沛槐</td>\n",
       "      <td>21</td>\n",
       "      <td>女</td>\n",
       "      <td>文科五班</td>\n",
       "      <td>564</td>\n",
       "      <td>2.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>1500100904</td>\n",
       "      <td>阎元蝶</td>\n",
       "      <td>23</td>\n",
       "      <td>女</td>\n",
       "      <td>文科五班</td>\n",
       "      <td>562</td>\n",
       "      <td>3.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>1500100136</td>\n",
       "      <td>黎昆鹏</td>\n",
       "      <td>22</td>\n",
       "      <td>男</td>\n",
       "      <td>文科六班</td>\n",
       "      <td>583</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>1500100900</td>\n",
       "      <td>查思菱</td>\n",
       "      <td>24</td>\n",
       "      <td>女</td>\n",
       "      <td>文科六班</td>\n",
       "      <td>562</td>\n",
       "      <td>2.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>1500100716</td>\n",
       "      <td>丰冷霜</td>\n",
       "      <td>22</td>\n",
       "      <td>女</td>\n",
       "      <td>文科六班</td>\n",
       "      <td>560</td>\n",
       "      <td>3.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>1500100873</td>\n",
       "      <td>路鸿志</td>\n",
       "      <td>24</td>\n",
       "      <td>男</td>\n",
       "      <td>文科四班</td>\n",
       "      <td>612</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>1500100258</td>\n",
       "      <td>湛昌勋</td>\n",
       "      <td>22</td>\n",
       "      <td>男</td>\n",
       "      <td>文科四班</td>\n",
       "      <td>604</td>\n",
       "      <td>2.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>1500100116</td>\n",
       "      <td>文元蝶</td>\n",
       "      <td>21</td>\n",
       "      <td>女</td>\n",
       "      <td>文科四班</td>\n",
       "      <td>520</td>\n",
       "      <td>3.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>1500100235</td>\n",
       "      <td>沈香巧</td>\n",
       "      <td>24</td>\n",
       "      <td>女</td>\n",
       "      <td>理科一班</td>\n",
       "      <td>520</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>1500100773</td>\n",
       "      <td>傅元蝶</td>\n",
       "      <td>21</td>\n",
       "      <td>女</td>\n",
       "      <td>理科一班</td>\n",
       "      <td>492</td>\n",
       "      <td>2.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>1500100925</td>\n",
       "      <td>卞乐萱</td>\n",
       "      <td>21</td>\n",
       "      <td>女</td>\n",
       "      <td>理科一班</td>\n",
       "      <td>486</td>\n",
       "      <td>3.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>1500100929</td>\n",
       "      <td>满慕易</td>\n",
       "      <td>21</td>\n",
       "      <td>女</td>\n",
       "      <td>理科三班</td>\n",
       "      <td>630</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>1500100184</td>\n",
       "      <td>夔寻巧</td>\n",
       "      <td>24</td>\n",
       "      <td>女</td>\n",
       "      <td>理科三班</td>\n",
       "      <td>580</td>\n",
       "      <td>2.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>1500100598</td>\n",
       "      <td>宰金鹏</td>\n",
       "      <td>24</td>\n",
       "      <td>男</td>\n",
       "      <td>理科三班</td>\n",
       "      <td>551</td>\n",
       "      <td>3.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>1500100834</td>\n",
       "      <td>谷念薇</td>\n",
       "      <td>21</td>\n",
       "      <td>女</td>\n",
       "      <td>理科二班</td>\n",
       "      <td>586</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>1500100104</td>\n",
       "      <td>咸冰蝶</td>\n",
       "      <td>23</td>\n",
       "      <td>女</td>\n",
       "      <td>理科二班</td>\n",
       "      <td>533</td>\n",
       "      <td>2.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>1500100762</td>\n",
       "      <td>聂德明</td>\n",
       "      <td>23</td>\n",
       "      <td>男</td>\n",
       "      <td>理科二班</td>\n",
       "      <td>524</td>\n",
       "      <td>3.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>1500100080</td>\n",
       "      <td>巫景彰</td>\n",
       "      <td>21</td>\n",
       "      <td>男</td>\n",
       "      <td>理科五班</td>\n",
       "      <td>628</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>1500100547</td>\n",
       "      <td>廖向南</td>\n",
       "      <td>22</td>\n",
       "      <td>女</td>\n",
       "      <td>理科五班</td>\n",
       "      <td>584</td>\n",
       "      <td>2.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>1500100839</td>\n",
       "      <td>明雁桃</td>\n",
       "      <td>22</td>\n",
       "      <td>女</td>\n",
       "      <td>理科五班</td>\n",
       "      <td>557</td>\n",
       "      <td>3.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>30</th>\n",
       "      <td>1500100596</td>\n",
       "      <td>田晨潍</td>\n",
       "      <td>21</td>\n",
       "      <td>男</td>\n",
       "      <td>理科六班</td>\n",
       "      <td>587</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>31</th>\n",
       "      <td>1500100903</td>\n",
       "      <td>於依云</td>\n",
       "      <td>24</td>\n",
       "      <td>女</td>\n",
       "      <td>理科六班</td>\n",
       "      <td>549</td>\n",
       "      <td>2.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>32</th>\n",
       "      <td>1500100563</td>\n",
       "      <td>禄昆鹏</td>\n",
       "      <td>22</td>\n",
       "      <td>男</td>\n",
       "      <td>理科六班</td>\n",
       "      <td>536</td>\n",
       "      <td>3.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>33</th>\n",
       "      <td>1500100635</td>\n",
       "      <td>蓬怀绿</td>\n",
       "      <td>23</td>\n",
       "      <td>女</td>\n",
       "      <td>理科四班</td>\n",
       "      <td>534</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>34</th>\n",
       "      <td>1500100590</td>\n",
       "      <td>逄中震</td>\n",
       "      <td>24</td>\n",
       "      <td>男</td>\n",
       "      <td>理科四班</td>\n",
       "      <td>530</td>\n",
       "      <td>2.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35</th>\n",
       "      <td>1500100939</td>\n",
       "      <td>耿智杰</td>\n",
       "      <td>23</td>\n",
       "      <td>男</td>\n",
       "      <td>理科四班</td>\n",
       "      <td>530</td>\n",
       "      <td>3.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    student_id name  age gender clazz  score  rank_res\n",
       "0   1500100308  黄初夏   23      女  文科一班    628       1.0\n",
       "1   1500100875  马向南   21      女  文科一班    595       2.0\n",
       "2   1500100943  许昌黎   21      男  文科一班    580       3.0\n",
       "3   1500100160  云冰真   24      女  文科三班    568       1.0\n",
       "4   1500100434  黎雨珍   23      女  文科三班    550       2.0\n",
       "5   1500100572  臧忆香   23      女  文科三班    550       3.0\n",
       "6   1500100418  蓟海昌   22      男  文科二班    611       1.0\n",
       "7   1500100823  宓新曦   22      男  文科二班    547       2.0\n",
       "8   1500100954  咸芷天   21      女  文科二班    533       3.0\n",
       "9   1500100930  闻运凯   24      男  文科五班    589       1.0\n",
       "10  1500100949  颜沛槐   21      女  文科五班    564       2.0\n",
       "11  1500100904  阎元蝶   23      女  文科五班    562       3.0\n",
       "12  1500100136  黎昆鹏   22      男  文科六班    583       1.0\n",
       "13  1500100900  查思菱   24      女  文科六班    562       2.0\n",
       "14  1500100716  丰冷霜   22      女  文科六班    560       3.0\n",
       "15  1500100873  路鸿志   24      男  文科四班    612       1.0\n",
       "16  1500100258  湛昌勋   22      男  文科四班    604       2.0\n",
       "17  1500100116  文元蝶   21      女  文科四班    520       3.0\n",
       "18  1500100235  沈香巧   24      女  理科一班    520       1.0\n",
       "19  1500100773  傅元蝶   21      女  理科一班    492       2.0\n",
       "20  1500100925  卞乐萱   21      女  理科一班    486       3.0\n",
       "21  1500100929  满慕易   21      女  理科三班    630       1.0\n",
       "22  1500100184  夔寻巧   24      女  理科三班    580       2.0\n",
       "23  1500100598  宰金鹏   24      男  理科三班    551       3.0\n",
       "24  1500100834  谷念薇   21      女  理科二班    586       1.0\n",
       "25  1500100104  咸冰蝶   23      女  理科二班    533       2.0\n",
       "26  1500100762  聂德明   23      男  理科二班    524       3.0\n",
       "27  1500100080  巫景彰   21      男  理科五班    628       1.0\n",
       "28  1500100547  廖向南   22      女  理科五班    584       2.0\n",
       "29  1500100839  明雁桃   22      女  理科五班    557       3.0\n",
       "30  1500100596  田晨潍   21      男  理科六班    587       1.0\n",
       "31  1500100903  於依云   24      女  理科六班    549       2.0\n",
       "32  1500100563  禄昆鹏   22      男  理科六班    536       3.0\n",
       "33  1500100635  蓬怀绿   23      女  理科四班    534       1.0\n",
       "34  1500100590  逄中震   24      男  理科四班    530       2.0\n",
       "35  1500100939  耿智杰   23      男  理科四班    530       3.0"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "top3"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "ce82ed5e",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>student_id</th>\n",
       "      <th>name</th>\n",
       "      <th>age</th>\n",
       "      <th>gender</th>\n",
       "      <th>clazz</th>\n",
       "      <th>score</th>\n",
       "      <th>rank_res</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1500100308</td>\n",
       "      <td>黄初夏</td>\n",
       "      <td>23</td>\n",
       "      <td>女</td>\n",
       "      <td>文科一班</td>\n",
       "      <td>628</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1500100160</td>\n",
       "      <td>云冰真</td>\n",
       "      <td>24</td>\n",
       "      <td>女</td>\n",
       "      <td>文科三班</td>\n",
       "      <td>568</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>1500100418</td>\n",
       "      <td>蓟海昌</td>\n",
       "      <td>22</td>\n",
       "      <td>男</td>\n",
       "      <td>文科二班</td>\n",
       "      <td>611</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>1500100930</td>\n",
       "      <td>闻运凯</td>\n",
       "      <td>24</td>\n",
       "      <td>男</td>\n",
       "      <td>文科五班</td>\n",
       "      <td>589</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>1500100136</td>\n",
       "      <td>黎昆鹏</td>\n",
       "      <td>22</td>\n",
       "      <td>男</td>\n",
       "      <td>文科六班</td>\n",
       "      <td>583</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>1500100873</td>\n",
       "      <td>路鸿志</td>\n",
       "      <td>24</td>\n",
       "      <td>男</td>\n",
       "      <td>文科四班</td>\n",
       "      <td>612</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>1500100235</td>\n",
       "      <td>沈香巧</td>\n",
       "      <td>24</td>\n",
       "      <td>女</td>\n",
       "      <td>理科一班</td>\n",
       "      <td>520</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>1500100929</td>\n",
       "      <td>满慕易</td>\n",
       "      <td>21</td>\n",
       "      <td>女</td>\n",
       "      <td>理科三班</td>\n",
       "      <td>630</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>1500100834</td>\n",
       "      <td>谷念薇</td>\n",
       "      <td>21</td>\n",
       "      <td>女</td>\n",
       "      <td>理科二班</td>\n",
       "      <td>586</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>1500100080</td>\n",
       "      <td>巫景彰</td>\n",
       "      <td>21</td>\n",
       "      <td>男</td>\n",
       "      <td>理科五班</td>\n",
       "      <td>628</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>30</th>\n",
       "      <td>1500100596</td>\n",
       "      <td>田晨潍</td>\n",
       "      <td>21</td>\n",
       "      <td>男</td>\n",
       "      <td>理科六班</td>\n",
       "      <td>587</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>33</th>\n",
       "      <td>1500100635</td>\n",
       "      <td>蓬怀绿</td>\n",
       "      <td>23</td>\n",
       "      <td>女</td>\n",
       "      <td>理科四班</td>\n",
       "      <td>534</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    student_id name  age gender clazz  score  rank_res\n",
       "0   1500100308  黄初夏   23      女  文科一班    628       1.0\n",
       "3   1500100160  云冰真   24      女  文科三班    568       1.0\n",
       "6   1500100418  蓟海昌   22      男  文科二班    611       1.0\n",
       "9   1500100930  闻运凯   24      男  文科五班    589       1.0\n",
       "12  1500100136  黎昆鹏   22      男  文科六班    583       1.0\n",
       "15  1500100873  路鸿志   24      男  文科四班    612       1.0\n",
       "18  1500100235  沈香巧   24      女  理科一班    520       1.0\n",
       "21  1500100929  满慕易   21      女  理科三班    630       1.0\n",
       "24  1500100834  谷念薇   21      女  理科二班    586       1.0\n",
       "27  1500100080  巫景彰   21      男  理科五班    628       1.0\n",
       "30  1500100596  田晨潍   21      男  理科六班    587       1.0\n",
       "33  1500100635  蓬怀绿   23      女  理科四班    534       1.0"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 对班级第一名做绘图\n",
    "top1 = top3[top3.rank_res == 1]\n",
    "top1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "5d39bdfb",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1600x900 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import seaborn as sns\n",
    "import matplotlib.pyplot as plt\n",
    "fig = plt.figure(figsize=(16,9))\n",
    "plt.rcParams['font.sans-serif'] = ['SimHei'] \n",
    "# sns.set_theme(style=\"whitegrid\")\n",
    "ax = sns.barplot(x=\"clazz\", y=\"score\", data=top1)\n",
    "ax.set_xlabel(\"班级\")\n",
    "ax.set_ylabel(\"成绩\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "id": "80bc9a90",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1600x900 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import seaborn as sns\n",
    "import matplotlib.pyplot as plt\n",
    "fig = plt.figure(figsize=(16,9))\n",
    "plt.rcParams['font.sans-serif'] = ['SimHei'] \n",
    "plt.ylim((450,700))\n",
    "# sns.set_theme(style=\"whitegrid\")\n",
    "ax = sns.barplot(x=\"clazz\", y=\"score\", hue=\"rank_res\", data=top3)\n",
    "ax.set_xlabel(\"班级\")\n",
    "ax.set_ylabel(\"成绩\")\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "fa983cae",
   "metadata": {},
   "outputs": [],
   "source": [
    "# 班级中男女比例图\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "id": "5b6b4e53",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>student_id</th>\n",
       "      <th>name</th>\n",
       "      <th>age</th>\n",
       "      <th>gender</th>\n",
       "      <th>clazz</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1500100001</td>\n",
       "      <td>施笑槐</td>\n",
       "      <td>22</td>\n",
       "      <td>女</td>\n",
       "      <td>文科六班</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1500100002</td>\n",
       "      <td>吕金鹏</td>\n",
       "      <td>24</td>\n",
       "      <td>男</td>\n",
       "      <td>文科六班</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1500100003</td>\n",
       "      <td>单乐蕊</td>\n",
       "      <td>22</td>\n",
       "      <td>女</td>\n",
       "      <td>理科六班</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1500100004</td>\n",
       "      <td>葛德曜</td>\n",
       "      <td>24</td>\n",
       "      <td>男</td>\n",
       "      <td>理科三班</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1500100005</td>\n",
       "      <td>宣谷芹</td>\n",
       "      <td>22</td>\n",
       "      <td>女</td>\n",
       "      <td>理科五班</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>995</th>\n",
       "      <td>1500100996</td>\n",
       "      <td>厉运凡</td>\n",
       "      <td>24</td>\n",
       "      <td>男</td>\n",
       "      <td>文科三班</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>996</th>\n",
       "      <td>1500100997</td>\n",
       "      <td>陶敬曦</td>\n",
       "      <td>21</td>\n",
       "      <td>男</td>\n",
       "      <td>理科六班</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>997</th>\n",
       "      <td>1500100998</td>\n",
       "      <td>容昆宇</td>\n",
       "      <td>22</td>\n",
       "      <td>男</td>\n",
       "      <td>理科四班</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>998</th>\n",
       "      <td>1500100999</td>\n",
       "      <td>钟绮晴</td>\n",
       "      <td>23</td>\n",
       "      <td>女</td>\n",
       "      <td>文科五班</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>999</th>\n",
       "      <td>1500101000</td>\n",
       "      <td>符瑞渊</td>\n",
       "      <td>23</td>\n",
       "      <td>男</td>\n",
       "      <td>理科六班</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>1000 rows × 5 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     student_id name  age gender clazz\n",
       "0    1500100001  施笑槐   22      女  文科六班\n",
       "1    1500100002  吕金鹏   24      男  文科六班\n",
       "2    1500100003  单乐蕊   22      女  理科六班\n",
       "3    1500100004  葛德曜   24      男  理科三班\n",
       "4    1500100005  宣谷芹   22      女  理科五班\n",
       "..          ...  ...  ...    ...   ...\n",
       "995  1500100996  厉运凡   24      男  文科三班\n",
       "996  1500100997  陶敬曦   21      男  理科六班\n",
       "997  1500100998  容昆宇   22      男  理科四班\n",
       "998  1500100999  钟绮晴   23      女  文科五班\n",
       "999  1500101000  符瑞渊   23      男  理科六班\n",
       "\n",
       "[1000 rows x 5 columns]"
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 加载分析数据\n",
    "import pandas as pd\n",
    "student=pd.read_csv(\"../data/students.csv\",names=['student_id','name','age','gender','clazz'])\n",
    "student"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "id": "9f6ab898",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>clazz</th>\n",
       "      <th>gender</th>\n",
       "      <th>cnt</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>文科一班</td>\n",
       "      <td>女</td>\n",
       "      <td>41</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>文科一班</td>\n",
       "      <td>男</td>\n",
       "      <td>31</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>文科三班</td>\n",
       "      <td>女</td>\n",
       "      <td>44</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>文科三班</td>\n",
       "      <td>男</td>\n",
       "      <td>50</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>文科二班</td>\n",
       "      <td>女</td>\n",
       "      <td>38</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>文科二班</td>\n",
       "      <td>男</td>\n",
       "      <td>49</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>文科五班</td>\n",
       "      <td>女</td>\n",
       "      <td>41</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>文科五班</td>\n",
       "      <td>男</td>\n",
       "      <td>43</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>文科六班</td>\n",
       "      <td>女</td>\n",
       "      <td>49</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>文科六班</td>\n",
       "      <td>男</td>\n",
       "      <td>55</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>文科四班</td>\n",
       "      <td>女</td>\n",
       "      <td>42</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>文科四班</td>\n",
       "      <td>男</td>\n",
       "      <td>39</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>理科一班</td>\n",
       "      <td>女</td>\n",
       "      <td>47</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>理科一班</td>\n",
       "      <td>男</td>\n",
       "      <td>31</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>理科三班</td>\n",
       "      <td>女</td>\n",
       "      <td>33</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>理科三班</td>\n",
       "      <td>男</td>\n",
       "      <td>35</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>理科二班</td>\n",
       "      <td>女</td>\n",
       "      <td>43</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>理科二班</td>\n",
       "      <td>男</td>\n",
       "      <td>36</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>理科五班</td>\n",
       "      <td>女</td>\n",
       "      <td>37</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>理科五班</td>\n",
       "      <td>男</td>\n",
       "      <td>33</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>理科六班</td>\n",
       "      <td>女</td>\n",
       "      <td>37</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>理科六班</td>\n",
       "      <td>男</td>\n",
       "      <td>55</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>理科四班</td>\n",
       "      <td>女</td>\n",
       "      <td>41</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>理科四班</td>\n",
       "      <td>男</td>\n",
       "      <td>50</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   clazz gender  cnt\n",
       "0   文科一班      女   41\n",
       "1   文科一班      男   31\n",
       "2   文科三班      女   44\n",
       "3   文科三班      男   50\n",
       "4   文科二班      女   38\n",
       "5   文科二班      男   49\n",
       "6   文科五班      女   41\n",
       "7   文科五班      男   43\n",
       "8   文科六班      女   49\n",
       "9   文科六班      男   55\n",
       "10  文科四班      女   42\n",
       "11  文科四班      男   39\n",
       "12  理科一班      女   47\n",
       "13  理科一班      男   31\n",
       "14  理科三班      女   33\n",
       "15  理科三班      男   35\n",
       "16  理科二班      女   43\n",
       "17  理科二班      男   36\n",
       "18  理科五班      女   37\n",
       "19  理科五班      男   33\n",
       "20  理科六班      女   37\n",
       "21  理科六班      男   55\n",
       "22  理科四班      女   41\n",
       "23  理科四班      男   50"
      ]
     },
     "execution_count": 47,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "gender_res = student.groupby(by=['clazz','gender'])['student_id'].count().reset_index()\n",
    "# rename中需要给定columns参数名\n",
    "gender_res.rename(columns={'student_id':\"cnt\"},inplace=True)\n",
    "gender_res"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "id": "ace1e8ac",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0     文科一班/女\n",
       "1     文科一班/男\n",
       "2     文科三班/女\n",
       "3     文科三班/男\n",
       "4     文科二班/女\n",
       "5     文科二班/男\n",
       "6     文科五班/女\n",
       "7     文科五班/男\n",
       "8     文科六班/女\n",
       "9     文科六班/男\n",
       "10    文科四班/女\n",
       "11    文科四班/男\n",
       "12    理科一班/女\n",
       "13    理科一班/男\n",
       "14    理科三班/女\n",
       "15    理科三班/男\n",
       "16    理科二班/女\n",
       "17    理科二班/男\n",
       "18    理科五班/女\n",
       "19    理科五班/男\n",
       "20    理科六班/女\n",
       "21    理科六班/男\n",
       "22    理科四班/女\n",
       "23    理科四班/男\n",
       "dtype: object"
      ]
     },
     "execution_count": 45,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "gender_res['clazz']+\"/\"+gender_res['gender']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "id": "de4c7ac7",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "\n",
    "# Pie chart, where the slices will be ordered and plotted counter-clockwise:\n",
    "labels = gender_res['clazz']+\"/\"+gender_res['gender']\n",
    "sizes = gender_res['cnt']\n",
    "# explode = (0, 0.1, 0, 0)  # only \"explode\" the 2nd slice (i.e. 'Hogs')\n",
    "\n",
    "fig1, ax1 = plt.subplots()\n",
    "ax1.pie(sizes,  labels=labels, autopct='%1.1f%%',\n",
    "        shadow=True, startangle=90)\n",
    "ax1.axis('equal')  # Equal aspect ratio ensures that pie is drawn as a circle.\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "ae13a17e",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "28eb307f",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.9"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}
